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About Thinking Machines The mission of Thinking Machines is to build AI that extends human will and judgment. We are training frontier models with Inkling, developing Tinker to let people make models their own, and…
Location: Remote (Europe Time Zone) Start date: ASAP Language: English Team: AI About the Role Our client is a European technology company operating a cloud and infrastructure platform, and we are looking for an AI…
Who we are Video is 90% of the world's data. Most of it is invisible to machines. TwelveLabs builds the intelligence layer to change that. Our multimodal AI models understand video the way humans do — across sight,…
Founded in 2025, Omnisent is a Munich-based defense technology company developing fully autonomous, Counter-UAS system. We are a small, high-output team from Cambridge, Imperial College, MIT, and BCG united by a…
Build and deploy AI-powered transport applications using LLMs, computer vision, and agentic systems to optimize Singapore’s land transport network.
Build and evaluate AI models (PyTorch/JAX) and help productionize them into APIs and batch workflows under senior guidance.
Build and deploy ML models for object detection and image enhancement on embedded platforms for AR helmets, drones, and robots used in defense and first-responder scenarios.
Design, train, and deploy ML models and data pipelines using PyTorch/TensorFlow and MLOps tools in a full lifecycle workflow.
Design AI/ML accelerator ASICs and storage solutions, defining I/O subsystems (PCIe/UCIe/CXL) and memory hierarchies for high-performance AI workloads.
Build and optimize AI-driven cybersecurity systems, integrating sensor data and ML models for edge and distributed environments.
Build and deploy efficient multimodal AI systems for Japanese enterprises, optimizing models for real-world latency, memory, and reliability constraints.
Develops and optimizes AI models for real-time identity verification, facial recognition, and object detection, deploying them across embedded, edge, and cloud systems.
Build and optimize on-device AI systems, deploying LLMs, VLMs, and AI Agents to PCs and end devices using Python/C++ and frameworks like PyTorch and OpenVINO.
Build and deploy scalable ML pipelines, real-time/batch inference systems, and LLM serving stacks for a fintech personalization engine in AWS.
Build and optimize ML perception models (object detection, tracking, prediction) for GM’s fallback autonomy stack using camera, lidar, and radar data to safely bring vehicles to a stop when primary autonomy fails.
Build and deploy AI/ML systems for drug discovery and patient care, including GenAI, RAG, and agents, using Python, cloud platforms, and MLOps/LLMOps pipelines.
Lead the design, quantization, and deployment of edge-native AI models and knowledge analytics engines for UK Defence, ensuring compliance with JSP 936 standards.
Build cloud/edge computer-vision models for wildfire detection and environmental monitoring using PyTorch and NVIDIA Jetson, deploying AI in real-world outdoor systems.
Build real-time wildfire-detection models and edge-AI pipelines using PyTorch, TensorRT, and Jetson; deploy optimized vision systems on PTZ cameras and cloud to spot smoke, vegetation, and assets.
Build and deploy secure AI-powered web apps in a restricted DoD environment using Python, React, and RAG pipelines with LLMs like Llama 3.
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